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BilalMuftuoglu
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deit-base-distilled-patch16-224-65-fold1

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  2. model.safetensors +1 -1
  3. runs/May21_22-06-10_804716d6a90a/events.out.tfevents.1716329170.804716d6a90a.958.10 +2 -2
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: facebook/deit-base-distilled-patch16-224
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - imagefolder
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: deit-base-distilled-patch16-224-65-fold1
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+ results:
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+ - task:
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+ name: Image Classification
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+ type: image-classification
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+ dataset:
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+ name: imagefolder
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+ type: imagefolder
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+ config: default
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+ split: train
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.8169014084507042
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # deit-base-distilled-patch16-224-65-fold1
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+
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+ This model is a fine-tuned version of [facebook/deit-base-distilled-patch16-224](https://huggingface.co/facebook/deit-base-distilled-patch16-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5417
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+ - Accuracy: 0.8169
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 100
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-------:|:----:|:---------------:|:--------:|
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+ | No log | 0.9231 | 3 | 0.7888 | 0.4930 |
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+ | No log | 1.8462 | 6 | 0.7159 | 0.5070 |
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+ | No log | 2.7692 | 9 | 0.7091 | 0.5070 |
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+ | 0.7703 | 4.0 | 13 | 0.6908 | 0.5352 |
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+ | 0.7703 | 4.9231 | 16 | 0.6527 | 0.6197 |
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+ | 0.7703 | 5.8462 | 19 | 0.6236 | 0.7324 |
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+ | 0.6435 | 6.7692 | 22 | 0.6357 | 0.6901 |
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+ | 0.6435 | 8.0 | 26 | 0.5442 | 0.7042 |
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+ | 0.6435 | 8.9231 | 29 | 0.5449 | 0.7183 |
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+ | 0.5366 | 9.8462 | 32 | 0.5124 | 0.7465 |
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+ | 0.5366 | 10.7692 | 35 | 0.5029 | 0.7042 |
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+ | 0.5366 | 12.0 | 39 | 0.5486 | 0.7183 |
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+ | 0.4577 | 12.9231 | 42 | 0.5394 | 0.6761 |
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+ | 0.4577 | 13.8462 | 45 | 0.5511 | 0.7465 |
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+ | 0.4577 | 14.7692 | 48 | 0.5794 | 0.6901 |
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+ | 0.4187 | 16.0 | 52 | 0.5368 | 0.7324 |
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+ | 0.4187 | 16.9231 | 55 | 0.4678 | 0.7887 |
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+ | 0.4187 | 17.8462 | 58 | 0.6597 | 0.7042 |
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+ | 0.3542 | 18.7692 | 61 | 0.4969 | 0.8169 |
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+ | 0.3542 | 20.0 | 65 | 0.7103 | 0.7324 |
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+ | 0.3542 | 20.9231 | 68 | 0.4979 | 0.7606 |
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+ | 0.3057 | 21.8462 | 71 | 0.5271 | 0.7324 |
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+ | 0.3057 | 22.7692 | 74 | 0.5357 | 0.7746 |
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+ | 0.3057 | 24.0 | 78 | 0.4847 | 0.7887 |
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+ | 0.2816 | 24.9231 | 81 | 0.5425 | 0.8310 |
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+ | 0.2816 | 25.8462 | 84 | 0.5239 | 0.8028 |
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+ | 0.2816 | 26.7692 | 87 | 0.4141 | 0.8310 |
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+ | 0.2881 | 28.0 | 91 | 0.4997 | 0.8028 |
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+ | 0.2881 | 28.9231 | 94 | 0.4216 | 0.8028 |
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+ | 0.2881 | 29.8462 | 97 | 0.4668 | 0.7887 |
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+ | 0.2421 | 30.7692 | 100 | 0.5904 | 0.7887 |
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+ | 0.2421 | 32.0 | 104 | 0.5240 | 0.7746 |
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+ | 0.2421 | 32.9231 | 107 | 0.9937 | 0.7606 |
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+ | 0.2402 | 33.8462 | 110 | 0.4989 | 0.8028 |
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+ | 0.2402 | 34.7692 | 113 | 0.7232 | 0.7887 |
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+ | 0.2402 | 36.0 | 117 | 0.4815 | 0.8451 |
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+ | 0.1862 | 36.9231 | 120 | 0.7431 | 0.7746 |
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+ | 0.1862 | 37.8462 | 123 | 0.4434 | 0.8028 |
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+ | 0.1862 | 38.7692 | 126 | 0.4760 | 0.7887 |
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+ | 0.1783 | 40.0 | 130 | 0.5006 | 0.7887 |
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+ | 0.1783 | 40.9231 | 133 | 0.4986 | 0.7887 |
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+ | 0.1783 | 41.8462 | 136 | 0.7947 | 0.7887 |
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+ | 0.1783 | 42.7692 | 139 | 0.4897 | 0.8310 |
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+ | 0.1685 | 44.0 | 143 | 0.7500 | 0.7606 |
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+ | 0.1685 | 44.9231 | 146 | 0.6053 | 0.7887 |
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+ | 0.1685 | 45.8462 | 149 | 0.4777 | 0.8169 |
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+ | 0.1779 | 46.7692 | 152 | 0.5800 | 0.7746 |
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+ | 0.1779 | 48.0 | 156 | 0.4681 | 0.8451 |
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+ | 0.1779 | 48.9231 | 159 | 0.7729 | 0.8028 |
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+ | 0.1502 | 49.8462 | 162 | 0.6487 | 0.8028 |
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+ | 0.1502 | 50.7692 | 165 | 0.5224 | 0.8169 |
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+ | 0.1502 | 52.0 | 169 | 0.7017 | 0.8028 |
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+ | 0.1586 | 52.9231 | 172 | 0.6034 | 0.8028 |
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+ | 0.1586 | 53.8462 | 175 | 0.5791 | 0.8028 |
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+ | 0.1586 | 54.7692 | 178 | 0.5651 | 0.8169 |
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+ | 0.134 | 56.0 | 182 | 0.4862 | 0.8028 |
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+ | 0.134 | 56.9231 | 185 | 0.6751 | 0.8169 |
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+ | 0.134 | 57.8462 | 188 | 0.5925 | 0.8169 |
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+ | 0.1602 | 58.7692 | 191 | 0.3982 | 0.8451 |
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+ | 0.1602 | 60.0 | 195 | 0.5969 | 0.7887 |
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+ | 0.1602 | 60.9231 | 198 | 0.5721 | 0.7887 |
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+ | 0.1217 | 61.8462 | 201 | 0.3816 | 0.8732 |
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+ | 0.1217 | 62.7692 | 204 | 0.4110 | 0.8310 |
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+ | 0.1217 | 64.0 | 208 | 0.6716 | 0.7887 |
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+ | 0.1274 | 64.9231 | 211 | 0.3499 | 0.8732 |
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+ | 0.1274 | 65.8462 | 214 | 0.3671 | 0.8169 |
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+ | 0.1274 | 66.7692 | 217 | 0.5318 | 0.7887 |
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+ | 0.1277 | 68.0 | 221 | 0.6734 | 0.7887 |
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+ | 0.1277 | 68.9231 | 224 | 0.4726 | 0.8028 |
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+ | 0.1277 | 69.8462 | 227 | 0.4311 | 0.8169 |
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+ | 0.1232 | 70.7692 | 230 | 0.7072 | 0.7746 |
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+ | 0.1232 | 72.0 | 234 | 0.5859 | 0.7887 |
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+ | 0.1232 | 72.9231 | 237 | 0.3758 | 0.8310 |
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+ | 0.1293 | 73.8462 | 240 | 0.3673 | 0.8451 |
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+ | 0.1293 | 74.7692 | 243 | 0.3673 | 0.8592 |
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+ | 0.1293 | 76.0 | 247 | 0.4752 | 0.8169 |
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+ | 0.1117 | 76.9231 | 250 | 0.4450 | 0.8310 |
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+ | 0.1117 | 77.8462 | 253 | 0.4437 | 0.8451 |
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+ | 0.1117 | 78.7692 | 256 | 0.4330 | 0.8310 |
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+ | 0.1092 | 80.0 | 260 | 0.5095 | 0.8169 |
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+ | 0.1092 | 80.9231 | 263 | 0.4948 | 0.8169 |
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+ | 0.1092 | 81.8462 | 266 | 0.4135 | 0.8592 |
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+ | 0.1092 | 82.7692 | 269 | 0.4190 | 0.8451 |
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+ | 0.1151 | 84.0 | 273 | 0.4194 | 0.8732 |
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+ | 0.1151 | 84.9231 | 276 | 0.4356 | 0.8310 |
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+ | 0.1151 | 85.8462 | 279 | 0.4623 | 0.8028 |
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+ | 0.1085 | 86.7692 | 282 | 0.4845 | 0.8310 |
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+ | 0.1085 | 88.0 | 286 | 0.4998 | 0.8169 |
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+ | 0.1085 | 88.9231 | 289 | 0.5181 | 0.8028 |
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+ | 0.0908 | 89.8462 | 292 | 0.5373 | 0.8169 |
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+ | 0.0908 | 90.7692 | 295 | 0.5465 | 0.8169 |
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+ | 0.0908 | 92.0 | 299 | 0.5422 | 0.8169 |
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+ | 0.0902 | 92.3077 | 300 | 0.5417 | 0.8169 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.0
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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